Trajectory Data Mining Dr Yu Zheng Lead Researcher

Trajectory Data Mining Dr. Yu Zheng Lead Researcher, Microsoft Research Chair Professor at Shanghai Jiao Tong University Editor in Chief of ACM Trans. Intelligent Systems and Technology http: //research. microsoft. com/en us/people/yuzheng/

Spatial Trajectories • Yu Zheng. Trajectory Data Mining: An Overview. ACM Transactions on Intelligent Systems and Technology. 2015, vol. 6, issue 3.

Sources of Trajectory Data • Human mobility – Active recording • • Travel logs Sport analysis Check ins … – Passive recording • • Credit card transactions Public transit records Mobile phone signal, Wi Fi… …. Yu Zheng. Trajectory Data Mining: An Overview. ACM Transactions on Intelligent Systems and Technology. 2015, vol. 6, issue 3.

Sources of Trajectory Data • Mobility of transportation vehicles – Taxis, buses, trucks, … – Air planes, ferries, cruise, … • Mobility of Animals – Migration: Birds, zebra, tiger • Mobility of natural phenomena – Hurricane, tornado, …

Paradigm of Trajectory Data Mining Yu Zheng. Trajectory Data Mining: An Overview. ACM Transactions on Intelligent Systems and Technology. 2015, vol. 6, issue 3.

Public Trajectory Datasets • Geo. Life Trajectory Dataset [159]: – • T Drive Taxi Trajectories [160]: – • This dataset is provided by the National Hurricane Service (NHS), containing 1, 740 trajectories of Atlantic Hurricanes (formally defined as tropical cyclone) from 1851 to 2012. NHS also provides annotations of typical hurric ane tracks for each month throughout the annual hurricane season that spans from June to November. The Greek truck trajectories [164]: – • The dataset consists of the check in data generated by over 49, 000 users in New York City and 31, 000 users in Los Angeles as well as the social structure of the users. Each check in includes a venue ID, the category of the venue, a timestamp, and a user ID. Hurricane trajectories [163]: – • Each trajectory has a set of transpor tation mode labels, such as driving, taking a bus, riding a bike and walking. Check in Data from Location based Social Networks [162]: – • A sample of trajectories from Microsoft Research T Drive project [123], generated by over 10, 000 taxicabs in a week of 2008 in Beijing. GPS Trajectory with Transportation Labels [161]: – • a GPS trajectory dataset from Microsoft Research Geo. Life project [153], collected by 182 users from April 2007 to August 2012. The dataset has been used to estimate the similarity between users [54], which enables friend and location recommendations [154][155]. This dataset contains 1, 100 trajectories from 50 different trucks delivering concrete around Athens, Greece. It was used to evaluate trajectory pattern mining task in [34]. Movebank animal tracking data [165]: – Movebank is a free, online database of animal tracking data, helping animal tracking researchers to manage, share, protect, analyze, and archive their data.

Important References • Yu Zheng. Trajectory Data Mining: An Overview. ACM Transactions on Intelligent Systems and Technology, vol. 6, issue 3, 2015. • Yu Zheng. Methodologies for Cross Domain Data Fusion: An Overview. IEEE Transactions on Big Data, vol. 1, no. 1. 2015. • Yu Zheng, Licia Capra, Ouri Wolfson, Hai Yang. Urban Computing: concepts, methodologies, and applications. ACM Transactions on Intelligent Systems and Technology, vol. 5, issue 3, pp. 38, 2014 • Yu Zheng, Xiaofang Zhou. Computing with Spatial Trajectories. Springer 2011. ISBN: 978 1 4614 1628 9 • Yu Zheng, Xing Xie, Wei Ying Ma, Geo. Life: A Collaborative Social Networking Service among User, location and trajectory. IEEE Data Engineering Bulletin. 33, 2, 2010, pp. 32 40.

Thanks! Yu Zheng yuzheng@microsoft. com Homepage Yu Zheng. Trajectory Data Mining: An Overview. ACM Transactions on Intelligent Systems and Technology. 2015, vol. 6, issue 3.